Design automation algorithms for advanced lithography

In circuit manufacturing, as the technology nodes keep shrinking, conventional 193 nm immersion lithography (193i) has reached its printability limit. To continue the scaling with Moore's law, different kinds of advanced lithography have been proposed, such as multiple patterning lithography (MPL), extreme ultraviolet (EUV), electron beam lithography (EBL) and directed self-assembly (DSA). While these new technologies create enormous opportunities, they also pose great design challenges due to their unique process characteristics and stringent constraints. In order to smoothly adopt these advanced lithography technologies in integrated circuit (IC) fabrication, effective electronic design automation (EDA) algorithms must be designed and integrated into computer-aided design (CAD) tools to address the underlying design constraints and help the circuit designer to better facilitate the lithography process. In this thesis, we focus on algorithmic design and efficient implementation of EDA algorithm for advanced lithography, including directed self-assembly (DSA) and self-aligned double patterning (SADP), to conquer the physical challenges and improve the manufacturing yield. The first advanced lithography technology we explore is self-aligned double patterning (SADP). SADP has the significant advantage over traditional litho-etch-litho-etch (LELE) double patterning in its ability to eliminate overlay, making it a preferable DPL choice for the 14 nm technology node. As in any DPL technology, layout decomposition is the key problem. While the layout decomposition problem for LELE DPL has been well studied in the literature, only a few attempts have been made for the SADP layout decomposition problem. This thesis studies the SADP decomposition problem in different scenarios. SADP has been successfully deployed in 1D patterns and has several applications; however, applying it to 2D patterns turns out to be much more difficult. All previous exact algorithms were based on computationally expensive methods such as SAT or ILP. Other previous algorithms were heuristics without a guarantee that an overlay-free solution can be found even if one exists. The SADP decomposition problem on general 2D layout is proven to be NP-complete. However, we show that if we restrict the overlay, the problem is polynomial-time solvable, and present an exact algorithm to determine if a given 2D layout has a no-overlay SADP decomposition. When designing the layout decomposition algorithms, it is usually useful to take the layout structure into consideration. As most of the current IC layouts adopt a row-based standard cell design style, we can take advantage of its characteristics and design more efficient algorithms compared to the algorithms for general 2D patterns. In particular, the fixed widths of standard cells and power tracks on top and bottom of cells suggest that improvements can be made over the algorithms for general decomposition problem. We present a shortest-path based polynomial time SADP decomposition algorithm for row-based standard cell layout that efficiently finds decompositions with minimum overlay violations. Our proposed algorithm takes advantage of the fixed width of the cells and the alternating power tracks between the rows to limit the possible decompositions and thus achieve high efficiency. The next advanced lithography technology we discuss in the thesis is directed self-assembly (DSA). Block copolymer directed self-assembly (DSA) is a promising technique for patterning contact holes and vias in 7 nm technology nodes. To pattern contacts/vias with DSA, guiding templates are usually printed first with conventional lithography (193i) that has a coarser pitch resolution. Contact holes are then patterned with DSA process. The guiding templates play the role of defining the DSA patterns, which have a finer resolution than the templates. As a result, different patterns can be obtained through controlling the templates. It is shown that DSA lithography is very promising in patterning contacts/vias in 7 nm technology node. However, to utilize DSA for full-chip manufacturing, EDA for DSA must be fully explored because EDA is the key enabler for manufacturing, and the EDA research for DSA is still lagging behind. To pattern the contact layer with DSA, we must ensure that all the contacts in the layout require only feasible DSA templates. Nevertheless, the original layout may not be designed in a DSA-friendly way. However, even with an optimized library, infeasible templates may be introduced after the physical design phase. We propose a simulated-annealing (SA) based scheme to perform full-chip level contact layer optimization. According to the experimental results, the DSA conflicts in the contact layer are reduced by close to 90% on average after applying the proposed optimization algorithm. It is a current trend that industry is transiting from the random 2D designs to highly regular 1D gridded designs for sub-20 nm nodes and fabricating circuit designs with print-cut technology. In this process, the randomly distributed cuts may be too dense to be printed by single patterning lithography. DSA has proven its success in contact hole patterning, and can be easily expanded to cut printing for 1D gridded designs. Nevertheless, the irregular distribution of cuts still presents a great challenge for DSA, as the self-assembly process usually forms regular patterns. As a result, the cut layer must be optimized for the DSA process. To address the above problem, we propose an efficient algorithm to optimize cut layers without hurting the original circuit logic. Our work utilizes a technique called `line-end extension' to move the cuts and extend the functional wires without changing the original functionality of the circuit. Consequently, the cuts can be redistributed and grouped into valid DSA templates. Multiple patterning lithography has been widely adopted for today's circuit manufacturing. However, increasing the number of masks will make the manufacturing process more expensive. By incorporating DSA into the multiple patterning process, it is possible to reduce the number of masks and achieve a cost-effective solution. We study the decomposition problem for the contact layer in row-based standard cell layout with DSA-MP complementary lithography. We explore several heuristic-based approaches, and propose an algorithm that decomposes a standard cell row optimally in polynomial-time. Our experiments show that our algorithm is guaranteed to find a minimum cost solution if one exists, while the heuristic cannot or only finds a sub-optimal solution. Our results show that the DSA-MP complementary approach is very promising for the future advanced nodes. As in any lithography technique, the process variation control and proximity correction are the most important issues. As the DSA templates are patterned by conventional lithography, the patterned templates are prone to deviate from mask shapes due to process variations, which will ultimately affect the contacts after the DSA process even for the same type of template. Therefore, in order to enable the DSA technology in contact/via layer printing, it is extremely important to accurately model and detect hotspots, as well as estimate the contact pitch and locations during the verification phase. We propose a machine learning based design automation framework for DSA verification. A novel DSA model and a set of features are included. We implemented the proposed ML-based flow and performed extensive experiments on comparing the performances of learning algorithms and features. The experimental results show that our approach is much more efficient than the traditional approach, and can produce highly accurate results

Scanning evanescent wave lithography for sub-22nm generations

Current assumptions for the limits of immersion optical lithography include NA values at 1.35, largely based on the lack of high-index materials. In this research we have been working with ultra-high NA evanescent wave lithography (EWL) where the NA of the projection system is allowed to exceed the corresponding acceptance angle of one or more materials of the system. This approach is made possible by frustrating the total internal reflection (TIR) evanescent field into propagation. With photoresist as the frustrating media, the allowable gap for adequate exposure latitude is in the sub-100 nm range. Through static imaging, we have demonstrated the ability to resolve 26 nm half-pitch features at 193 nm and 1.85 NA using existing materials. Such imaging could lead to the attainment of 13 nm half-pitch through double patterning. In addition, a scanning EWL imaging system was designed, prototyped with a two-stage gap control imaging head including a DC noise canceling carrying air-bearing, and a AC noise canceling piezoelectric transducer with real-time closed-loop feedback from gap detection. Various design aspects of the system including gap detection, feedback actuation, prism design and fabrication, software integration, and scanning scheme have been carefully considered to ensure sub-100 nm scanning. Experiments performed showed successful gap gauging at sub-100 nm scanning height. Scanning EWL results using a two-beam interference imaging approach achieved pattern resolution comparable to static EWL imaging results. With this scanning EWL approach and the imaging head developed, optical lithography becomes extendable to sub-22 nm generations

Advanced Rotorcraft Transmission (ART) program

Work performed by the McDonnell Douglas Helicopter Company and Lucas Western, Inc. within the U.S. Army/NASA Advanced Rotorcraft Transmission (ART) Program is summarized. The design of a 5000 horsepower transmission for a next generation advanced attack helicopter is described. Government goals for the program were to define technology and detail design the ART to meet, as a minimum, a weight reduction of 25 percent, an internal noise reduction of 10 dB plus a mean-time-between-removal (MTBR) of 5000 hours compared to a state-of-the-art baseline transmission. The split-torque transmission developed using face gears achieved a 40 percent weight reduction, a 9.6 dB noise reduction and a 5270 hour MTBR in meeting or exceeding the above goals. Aircraft mission performance and cost improvements resulting from installation of the ART would include a 17 to 22 percent improvement in loss-exchange ratio during combat, a 22 percent improvement in mean-time-between-failure, a transmission acquisition cost savings of 23 percent of $165K, per unit, and an average transmission direct operating cost savings of 33 percent, or$24K per flight hour. Face gear tests performed successfully at NASA Lewis are summarized. Also, program results of advanced material tooth scoring tests, single tooth bending tests, Charpy impact energy tests, compact tension fracture toughness tests and tensile strength tests are summarized

Computational Design Of Protein–ligand And Protein–protein Interactions

Central to the function of proteins is the concept of molecular recognition. Protein–ligand and protein–protein interactions make up the bulk of the chemical processes that give rise to living things. Realizing the full potential of protein design technology will therefore require an increased understanding of the design principles of molecular recognition. We have tackled problems involving molecular recognition by using computational methods to design novel protein-ligand and protein-protein interactions. Firstly, we set out to design a protein capable of recognizing lanthanide metal ions. Protein-lanthanide systems are of interest for their potential to serve as purification agents for use under biological conditions. We have designed a highly dense 6-coordinate lanthanide binding at the core of a de novo protein, and used the dynamical aspects of the protein to achieve a degree of differentiation between elements in the lanthanide series. Secondly, we investigated systems of homo-oligomeric protein complexes that self-assemble into hollow cages. We have studied the structural determinants of naturally occurring self-assembling ferritin cages and identified a single mutation that greatly increased the stability of the ferritin cage, as well as dramatically altered the overall structure of the assembly. We have also used the formulation of probabilistic protein design to arrive at novel sequences for α-helical peptides that can adjust their surfaces in accordance to different local environments. This formulation was used to identify a sequence for a peptide designed to self-assemble into a spherical particle with broken symmetry. Taken together, these efforts will lead to an increased understanding of the role of kinetics and structural plasticity in protein-ligand and protein-protein interactions

Low-cost, bottom-up fabrication of large-scale single-molecule nanoarrays by DNA origami placement

Large-scale nanoarrays of single biomolecules enable high-throughput assays while unmasking the underlying heterogeneity within ensemble populations. Until recently, creating such grids which combine the unique advantages of microarrays and single-molecule experiments (SMEs) has been particularly challenging due to the mismatch between the size of these molecules and the resolution of top-down fabrication techniques. DNA Origami Placement (DOP) combines two powerful techniques to address this issue: (i) DNA origami, which provides a 100-nm self-assembled template for single-molecule organization with 5 nm resolution, and (ii) top-down lithography, which patterns these DNA nanostructures, transforming them into functional nanodevices via large-scale integration with arbitrary substrates. Presently, this technique relies on state-of-the-art infrastructure and highly-trained personnel, making it prohibitively expensive for researchers. Here, we introduce a bench-top technique to create meso-to-macro-scale DNA origami nanoarrays using self-assembled colloidal nanoparticles, thereby circumventing the need for top-down fabrication. We report a maximum yield of 74%, two-fold higher than the statistical limit of 37% imposed on non-specific molecular loading alternatives. Furthermore, we provide a proof-of-principle for the ability of this nanoarray platform to transform traditionally low-throughput, stochastic, single-molecule assays into high-throughput, deterministic ones, without compromising data quality. Our approach has the potential to democratize single-molecule nanoarrays and demonstrates their utility as a tool for biophysical assays and diagnostics

Fabrication and Dynamic Tuning of Periodic Structures From Holographic Lithography

In this dissertation, I fabricated one-dimensional (1D), two-dimensional (2D) and three-dimensional (3D) periodic structures through holographic lithography (HL) and backfilling conversion with different materials. Along the line, I investigated their intrinsic structure-property relationship, harness and utilize the mechanical instability, and explored novel applications as tunable periodic structures. In order to mimic butterfly wings which show both structural color and superhydrophobicity, 3D diamond photonic crystals with controllable nano-roughness (≤ 120 nm) were fabricated from epoxy-functionalized cyclohexyl polyhedral oligomeric silsesquioxanes (epoxy-POSS). The nano-roughness was generated due to microphase separation of the polymer chain segments in nonsolvents during rinsing, which could be tuned by crosslinking density of the polymer and choice of solvents. Such structure offers opportunities to realize superhydrophobicity, enhanced dye adsorption in addition to the photon management in the 3D photonic crystal. Most of current studies on tunable periodic structures show limited tunable optical property ranges, which is attractive to be expanded. 2D shape memory polymer (SMP) membranes consisting of a hexagonal array of micron-sized holes were fabricated by converting from epoxy-POSS template. Reversible color switching from transparency to colorful state was achieved through thermal-mechanical deformation, utilizing shape memory effect and mechanical instability induced pattern transformation. Continuum mechanical analyses corroborated well with experimental observations. Potential applications as displays were demonstrated via two different approaches. It is challenging to directly fabricate high aspect-ratio (AR) 1D nano-scale structures, due to depth-of-focus (DOF) limitation, pattern collapse from capillary force and distortion during solvent swelling. With HL and supercritical drying, high AR 1D nano-scale structures were fabricated with epoxy-POSS and SU-8, which avoid DOF limitation and pattern collapse. Due to enhanced thermal and mechanical stability of epoxy-POSS, 1D nanogratings (AR up to 10) with controllable periodicity, filling fraction and surface roughness, were achieved, which could be directly converted to silica-like through calcination. By exploiting swelling-induced buckling of 1D SU-8 nanowalls with nanofibers formed in-between, long-range ordered 2D nanowaves with weaker reflecting color were achieved, where degree of lateral undulation could be controlled by tuning AR and exposure dosage. Using double-exposure through photomasks, patterns with both nanowaves and nanowalls for optical display were created

Advances on Mechanics, Design Engineering and Manufacturing III

This open access book gathers contributions presented at the International Joint Conference on Mechanics, Design Engineering and Advanced Manufacturing (JCM 2020), held as a web conference on June 2–4, 2020. It reports on cutting-edge topics in product design and manufacturing, such as industrial methods for integrated product and process design; innovative design; and computer-aided design. Further topics covered include virtual simulation and reverse engineering; additive manufacturing; product manufacturing; engineering methods in medicine and education; representation techniques; and nautical, aeronautics and aerospace design and modeling. The book is organized into four main parts, reflecting the focus and primary themes of the conference. The contributions presented here not only provide researchers, engineers and experts in a range of industrial engineering subfields with extensive information to support their daily work; they are also intended to stimulate new research directions, advanced applications of the methods discussed and future interdisciplinary collaborations

Research and technology, 1992

Selected research and technology activities at Ames Research Center, including the Moffett Field site and the Dryden Flight Research Facility, are summarized. These activities exemplify the Center's varied and productive research efforts for 1992

Computational Modeling and Design of Protein and Polymeric Nano-Assemblies

Advances in nanotechnology have the potential to utilize biological and polymeric systems to address fundamental scientific and societal issues, including molecular electronics and sensors, energy-relevant light harvesting, â??greenâ?? catalysis, and environmental cleanup. In many cases, synthesis and fabrication are well within grasp, but designing such systems requires simultaneous consideration of large numbers of degrees of freedom including structure, sequence, and functional properties. In the case of protein design, even simply considering amino acid identity scales exponentially with the protein length. This work utilizes computational techniques to develop a fundamental, molecularly detailed chemical and physical understanding to investigate and design such nano-assemblies. Throughout, we leverage a probabilistic computational design approach to guide the identification of protein sequences that fold to predetermined structures with targeted function. The statistical methodology is encapsulated in a computational design platform, recently reconstructed with improvements in speed and versatility, to estimate site-specific probabilities of residues through the optimization of an effective sequence free energy. This provides an information-rich perspective on the space of possible sequences which is able to harness the incorporation of new constraints that fit design objectives. The approach is applied to the design and modeling of protein systems incorporating non-biological cofactors, namely (i) an aggregation prone peptide assembly to bind uranyl and (ii) a protein construct to encapsulate a zinc porphyrin derivative with unique photo-physical properties. Additionally, molecular dynamics simulations are used to investigate purely synthetic assemblies of (iii) highly charged semiconducting polymers that wrap and disperse carbon nanotubes. Free energy calculations are used to explore the factors that lead to observed polymer-SWNT super-structures, elucidating well-defined helical structures; for chiral derivatives, the simulations corroborate a preference for helical handedness observed in TEM and AFM data. The techniques detailed herein, demonstrate how advances in computational chemistry allot greater control and specificity in the engineering of novel nano-materials and offer the potential to greatly advance applications of these systems